Electrocardiogram P-wave sign is related to new-onset atrial fibrillation of patients with acute myocardial infarction

doi:10.16352/j.issn.1001-6325.2024.11.1569

Abstract

Abstract: Objective To investigate the relationship between dynamic electrocardiogram P-wave sign and new-onset atrial fibrillation (NOAF) in patients with acute myocardial infarction (AMI)(AMI-NOAF). Methods Totally 240 patients with AMI admitted to Wuwei Cancer Hospital were examined by dynamic electrocardiogram. P-wave sign parameters and clinical data of holter electrocardiogram were collected. The relationship between P-wave sign and clinical parameters of AMI patients was analyzed. The patients were divided into NOAF group and nonoccurrence(non-NOAF) group and multivariate Logistic regression model was used to identify the influencing factors of NOAF occurrence in AMI. Results Killip Ⅲ-Ⅳ grade minimum P wave duration (P_min) level was shorter than that of Ⅰ-Ⅱ grade. Maximum P wave duration (P_max) and P wave dispersion (Pd) level were higher than that of Ⅰ-Ⅱ grade(P＜0.05). NOAF occurred in 47 of 240 AMI patients (19.58%). The level of P_min in NOAF group was lower than that in non-NOAF group, and the level of P_max and Pd in NOAF group was higher than that in non-NOAF group(P＜0.05). The heart rate and the proportion of Killip grade Ⅲ-Ⅳ in NOAF group were higher than those in non-NOAF group(P＜0.05). Multivariate Logistic regression analysis showed that Killip Ⅲ-Ⅳgrade, high level of P_max and Pd were independent risk factors for NOAF in AMI (P＜0.05). Conclusions The level of P_min, P_max and Pd are correlated with Killip grading in AMI patients. AMI-NOAF patients have abnormal P-wave sign in holter electrocardiogram. The high levels of P_max and Pd are independent risk factors of AMI and NOAF.

Key words: acute myocardial infarction, atrial fibrillation, dynamic electrocardiogram, P-wave sign, conduction block

CLC Number:

R541.7+5

YANG Duojun, LIU Jinghan. Electrocardiogram P-wave sign is related to new-onset atrial fibrillation of patients with acute myocardial infarction[J]. Basic & Clinical Medicine, 2024, 44(11): 1569-1572.

References

[1] Saito Y, Oyama K, Tsujita K, et al. Treatment strategies of acute myocardial infarction: updates on revascularization, pharmacological therapy, and beyond[J]. J Cardiol, 2023,81:168-178.
[2] Frampton J, Ortengren AR, Zeitler EP. Arrhythmias after acute myocardial infarction[J]. Yale J Biol Med, 2023,96:83-94.
[3] Obayashi Y, Shiomi H, Morimoto T, et al. Newly diagnosed atrial fibrillation in acute myocardial infarctionet[J]. J Am Heart Assoc, 2021,10:e021417. doi: 10.1161/JAHA.121.021417.
[4] Duca şT, Roca M, Costache AD, et al. T-wave analysis on the 24 h holter ECG monitoring as a predictive assessment of major adverse cardiovascular events in patients with myocardial infarction: a literature review and future perspectiveset[J]. Life (Basel), 2023,13:1155. doi: 10.3390/life13051155.
[5] Gasperetti A, Cappelletto C, Carrick R, et al. Associa-tion of premature ventricular contraction burden on serial Holter monitoring with arrhythmic risk in patients with arrhythmogenic right ventricular cardiomyopathyet[J]. JAMA Cardiol, 2022,7:378-385.
[6] 潘昌,张航,钱伟春,等. Tp-e间期、P波离散度对室性心律失常病情的预测价值[J]. 现代生物医学进展,2021,21:2661-2664,2669.
[7] Kodani E. New-onset atrial fibrillation before or after myocardial infarction, Which is worse for mortality?[J]. Am J Cardiol, 2024,211:358-359.
[8] He K, Liang W, Liu S, et al. Long-term single-lead electrocardiogram monitoring to detect new-onset postoperative atrial fibrillation in patients after cardiac surgery[J]. Front Cardiovasc Med, 2022,9:1001883. doi: 10.3389/fcvm.2022.1001883.
[9] Carmona Puerta R, Lorenzo Martínez E, Rabassa López-Calleja MA, et al. New parameter of the second half of the P-wave, P-wave duration, and atrial conduction times predict atrial fibrillation during electrophysiological studies[J]. Med Princ Pract, 2021,30:462-469..
[10] 刘莉莉,冯雷,王立君,等. 急性心肌梗死患者住院期间新发心房颤动的危险因素研究[J]. 实用心脑肺血管病杂志,2021,29:38-41.
[11] Tzou HA, Lin SF, Chen PS. Paroxysmal atrial fibrillation prediction based on morphological variant P-wave analysis with wideband ECG and deep learning[J]. Comput Methods Programs Biomed, 2021,11:106396. doi: 10.1016/j.cmpb.2021.106396.